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Lithuanian Regional Fdi During the Litas Period, 1997-2013

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Lithuanian Regional Fdi During the Litas Period, 1997-2013 Journal of International Business Research Volume 17, Issue 1, 2018 LITHUANIAN REGIONAL FDI DURING THE LITAS PERIOD, 1997-2013 Gregory J Brock, Georgia Southern University ABSTRACT FDI in to the ten counties of Lithuania 1997-2013 is substantial and widely dispersed. Applying a standard model of FDI impact on regional economic growth reveals dispersion of FDI as well as the amount has contributed to stronger regional growth. Results are not sensitive to the uniqueness of greater Vilnius though the county with the national capital continues to attract the most FDI and has suffered least from the demographic crisis. Greater attention to human capital development outside of greater Vilnius is recommended to continue to attract FDI to rural areas of the country with a focus on new goods exports to enhance labour productivity. Keywords: Lithuania, Local FDI, Regional Analysis. JEL: F3, P2, P25 INTRODUCTION The inflow of Foreign Direct Investment (FDI) in to a small transition economy experiencing high emigration is understudied with Lithuania having the most challenging demographic crisis of any country in Europe (IMF, 2015). Once FDI arrives in a transition country it is often concentrated in a few urban areas leading to large inequalities across and within regions. Lithuania is no exception with the three counties with the three major cities having much better labour markets than other counties especially rural areas (OECD, 2018). While regional FDI is examined in the literature, how much FDI flows to urban centres versus rural areas is often ignored. Here we examine rural and urban FDI inside Lithuanian’s counties as the economy recovers from the 1998 financial crisis and through the Great Recession some 10 years later using a standard approach to FDI inflows applied to other countries but never Lithuania. Our analysis begins in the late 1990s due to data constraints before 1997 and ends in 2013. The sample period includes joining NATO in 2004 and ends just before the full adaption of the euro in late 2014 (Table 1). By 2014, Lithuania has successfully diversified in to new markets with a competitive economy that is predicted (IMF, 2015) to weather the crisis to the east well. Lithuania’s ten counties vary greatly in size and history. In the interwar period, Vilnius city and county were part of Poland with the capital moved to Kaunas. In the Soviet era, internal and external borders were quite open all around but the economy was distorted toward being a small piece of the overall Soviet economy. Since independence in 1991, external borders are quite open except the most western counties of Klaipeda, Marijampole and Taurage that border the Russian region of Kaliningrad where though the border is open, long delays are required to cross over. The three main cities of Lithuania-Vilnius, Kaunas and Klaipeda-all dominate their particular county’s economy with Klaipeda also benefitting from being the main port of the country. FDI positively impacts county growth but only Vilnius County has both above average accumulated FDI stock growth and per capita RGCP growth. Data on counties are important 1 1544-0230-17-1-108 Journal of International Business Research Volume 17, Issue 1, 2018 enough to warrant a separate statistical handbook before all data were made available online (Lietuvos Statistikos Departamentas, 2012). Prior cross-county analysis covering 2000-2011 only illustrated how uneven FDI has been across the ten counties, but ignored dispersion within a given county and used a different model (Sakalauskaite and Miskinis, 2014). Table 1 FOREIGN DIRECT INVESTMENT (FDI) IN LITHUANIAN COUNTIES, 1997-2013 Accumulated Real FDI (millions 2004 1997 1998 1999 2000 2001 2002 2003 Litas) Lithuania 4439.23 6623.05 8337.07 9311.45 10535.01 13044.57 13645 Avg. Annual Growth 39.50% 22.90% 11.00% 12.30% 21.30% 4.50% % County (apskritis) Alytus apskritis 117.98 177.6 217.62 222.11 147.44 141.76 191.88 Kaunas apskritis 678.23 820.42 1070.63 1231.69 1314.43 1579.69 1871.59 Klaipeda apskritis 765 880.51 1065.79 1164.77 1298.48 1367.35 1565.97 Marijampole 19.06 21.54 21.42 27.15 61.48 73.89 79.04 apskritis Panevezys apskritis 246.7 346.46 393.02 387.99 454.46 461.64 686.64 Siauliai apskritis 123.27 152.57 147.67 157.84 166.3 179.82 189.45 Taurage apskritis 13.7 18.29 25.47 21.97 19.56 14.66 22.87 Telsiai apskritis 130.2 119.14 170.51 87.46 17.15 557.92 777.11 Utena apskritis 7.28 94.4 97.79 111.16 205.62 336.64 254.72 Vilnius apskritis 2337.81 3992.13 5127.14 5899.31 6850.09 8331.19 8005.73 2004 2005 2006 2007 2008 2009 2010 Lithuania 15968.1 23025.07 26787.66 30919 23911.98 22409.44 24013.54 Avg. Annual Growth 15.70% 36.20% 15.10% 14.30% -25.60% -6.50% 6.90% % County (apskritis) Alytus apskritis 170.6 386.29 390.5 391.51 287.53 251.01 227.19 Kaunas apskritis 1886.9 2517.3 2298.63 3450.25 2452.57 2914.91 2891.63 Klaipeda apskritis 1743.3 2103.16 2020.36 2540.84 2506.4 2246.63 2369.19 Marijampole 112 98.18 92.01 81.57 106.12 231.54 234.62 apskritis Panevezys apskritis 728.3 665.73 488.69 517.29 439.79 552.18 433.07 Siauliai apskritis 193.7 269.41 362.79 381.66 376.96 352.76 394.4 Taurage apskritis 21.5 26.3 30.33 55.82 43.76 34.52 31.77 Telsiai apskritis 1171.6 3725.84 5912.24 5166.94 1161.57 1901.93 2525.56 Utena apskritis 218.4 259.47 224.36 289.98 261.69 253.76 246.65 Vilnius apskritis 9721.8 12973.39 14967.76 18043.15 16275.58 13670.19 14659.45 2004- 2012 2013 2013 Lithuania 26060.57 26846.35 Avg. Annual Growth 5.00% 3.00% % 2 1544-0230-17-1-108 Journal of International Business Research Volume 17, Issue 1, 2018 County (apskritis) Alytus apskritis 243.07 244.58 69.83% Kaunas apskritis 3302.85 2800.52 122.01% Klaipeda apskritis 2282.18 2090.41 92.83% Marijampole 297.66 259.78 172.65% apskritis Panevezys apskritis 531.72 623.79 86.64% Siauliai apskritis 383.35 394.62 104.79% Taurage apskritis 30.2 36.26 90.30% Telsiai apskritis 2290.27 2114.41 176.80% Utena apskritis 186.78 161.07 182.70% Vilnius apskritis 16512.49 18120.9 154.29% There has been great variation in FDI inflows. Starting from a low $30 million in the early 1990s, FDI increased steadily up to $925 million in 1998 but then was cut by 50% thanks to the Russian financial crisis at the end of that year. By the last year before NATO accession (2003) FDI was little more than the 1996 level. Joining NATO in 2004 strongly increased FDI to new highs with approximately $2 billion in FDI for each year 2006-2008 which some have characterized as excessive dependence (Jimborean and Kelber, 2017). However, the global crisis reduced 2009 to a level ($17 million) not seen since 1992 followed by a moderate recovery to $708 million in 2013. From 2007-2013 FDI has been found to enhance both GDP and export growth in both the short run period 2007-2013 (Gaspareniene and Remeikene, 2015) and over the entire transition period (Jimborean and Kelber, 2017). Unfortunately the crisis in nearby Ukraine now makes it unlikely FDI will return to the $2 billion level before the Great Recession. County (Apskritys) Descriptive Statistics Like the country overall, each county experienced strong real GCP growth over the entire Sample period with slightly slower growth after 2004 (Table 2). The demographic crisis then raised the per capita RGCP rates even higher overall and in the two shorter periods as well. Therefore population cannot be used as a proxy for economic output as is often done in the FDI literature. The severe demographic crisis warrants a more detailed description (Table 2). The population shares of counties are remarkably constant except for Vilnius County which increased from 24% to 27% of the inter-county share over the 17 year period. From 1996-2003 counties lost an average of 5% of their population with Utena losing the most (8.5%). Over the long run (1996-2013) counties lost 19.3% of their population with Utena again losing the most (30.9%). Only Klaipeda and Vilnius were below the long run average population loss with Vilnius losing only 7% which is an outlier. Therefore though all counties lost population, Vilnius alone gained a greater share of the smaller total. Lithuania is a classic case where a demographic crisis creates the appearance of a rising standard of living as measured by per capita GDP when actually the severe loss of population could lower the standard of living. Though growth is strong overall and recovered quickly after the Great Recession, the annual and persistent loss of 1% of the population during the 21st century (OECD, 2018) haunts any positive prognosis for future Lithuanian economic success. 3 1544-0230-17-1-108 Journal of International Business Research Volume 17, Issue 1, 2018 Table 2 GCP, POPULATION, FDI GROWTH RATES COMPARISON RGCP pcRGCP Pop. RFDI Stock Human growth Growth Growth Growth Capital 1997-2003 LITHUANIA 11.20% 11.90% -5.00% 101.80% 20.50% Alytus 9.40% 10.30% -6.00% 47.70% 14.20% Kaunas 12.00% 12.70% -5.30% 93.60% 23.70% Klaipeda 11.80% 12.50% -4.40% 68.70% 20.70% Marijampole 9.20% 9.90% -4.70% 122.30% 13.30% Panevezys 9.00% 9.90% -6.70% 94.30% 15.60% Siauliai 8.80% 9.80% -6.90% 42.30% 16.80% Taurage 8.60% 9.30% -4.80% 50.10% 13.70% Telsiai 12.00% 12.60% -4.20% 142.60% 12.10% Utena 9.30% 10.50% -8.50% 188.90% 17.50% Vilnius 15.20% 15.60% -2.90% 109.60% 27.00% RGCP pcRGCP Pop.
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